ABSTRACT
PURPOSE: To present our experience of cases of pulmonary sarcoidosis with atypical HRCT patterns found during 2016 focusing on the differential diagnosis to contribute to the difficult role of the radiologist in the disease identification and to help the clinicians to reach the diagnosis. MATERIALS AND METHODS: The HRCT examinations of 47 patients with sarcoidosis were studied retrospectively. All patients had a histopathological confirm of the disease. 29 (61.7%) show a typical pulmonary pattern and 18 (38.3%) an atypical pattern. The latter were evaluated by three experienced radiologists dedicated to thoracic disease to radiologically define the predominant pattern of presentation. RESULTS: In the 18 patients (38.3%) with atypical sarcoidosis, the following parenchymal patterns were observed: four patients (22.2%) had interstitial fibrotic alterations, three patients (16.6%) with reticular pattern with inter-intralobular septal thickening, two patients (11.1%) with small-airway involvement with mosaic oligoemia, two patients (11.1%) with pleural involvement (pneumothorax and pleural plaques), one patient (5.5%) with fibrocystic changes, 1 (5.5%) with halo-sign, 1 (5.5%) with diffuse bilateral ground-glass opacities, and 1 (5.5%) with isolated lung mass; in addition, three patients (16.6%) with atypical lymph node pattern were also found. CONCLUSIONS AND DISCUSSION: The atypical pulmonary alterations found in CT examination can be confused with other lung diseases and they are always a challenge even for the most experienced radiologist. In our experience, cases with atypical pulmonary sarcoidosis patterns evaluated in the study are consistent with similar cases described in the literature, both in lymph node and atypical parenchymal involvement. All the atypical characteristics of the work should alert the radiologist to consider sarcoidosis among the possible differential diagnoses, always correlating the results of the computed tomography examination with appropriate clinical-laboratory evaluations.
Subject(s)
Sarcoidosis, Pulmonary/diagnostic imaging , Sarcoidosis, Pulmonary/pathology , Tomography, X-Ray Computed/methods , Adult , Aged , Aged, 80 and over , Diagnosis, Differential , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , Sarcoidosis, Pulmonary/diagnosis , Sensitivity and SpecificityABSTRACT
This article aims to detect lung cavitations using lung ultrasound (LUS) in a cohort of patients with pulmonary tuberculosis (TB) and correlate the findings with chest computed tomography (CT) and chest X-ray (CXR) to obtain LUS diagnostic sensitivity. Patients with suspected TB were enrolled after being evaluated with CXR and chest CT. A blinded radiologist performed LUS within 3 days after admission at the Infectious Diseases Department. Finally, 82 patients were enrolled in this study. Bronchoalveolar lavage (BAL) confirmed TB in 58/82 (71%). Chest CT showed pulmonary cavitations in 38/82 (43.6%; 32 TB patients and 6 non-TB ones), LUS in 15/82 (18.3%; 11 TB patients and 4 non-TB ones) and CXR in 27/82 (33%; 23 TB patients and 4 non-TB ones). Twelve patients with multiple cavitations were detected with CT and only one with LUS. LUS sensitivity was 39.5%, specificity 100%, PPV 100% and NPV 65.7%. CXR sensitivity was 68.4% and specificity 97.8%. No false positive cases were found. LUS sensitivity was rather low, as many cavitated consolidations did not reach the pleural surface. Aerated cavitations could be detected with LUS with relative confidence, highlighting a thin air crescent sign towards the pleural surface within a hypoechoic area of consolidation, easily distinguishable from a dynamic or static air bronchogram.
ABSTRACT
OBJECTIVES: Patients with connective tissue diseases can develop interstitial lung disease (ILD), leading to a progressive fibrosing ILD (PF-ILD) phenotype in some cases. We aimed to investigate the occurrence of PF-ILD in idiopathic inflammatory myopathies (IIMs), and factors potentially predicting this phenotype. Secondary aims were to assess the radiological pattern and factors associated with IIMs-ILD. METHODS: Patients with IIMs from our multicentric prospective cohort were retrospectively evaluated. Data were recorded at IIMs and ILD diagnosis, and during follow-up. Patients with ILD were classified according to the predominant high-resolution CT (HRCT) pattern: non-specific interstitial pneumonia (NSIP), usual interstitial pneumonia (UIP) and organising pneumonia (OP). PF-ILD was defined according to the 2022 American Thoracic Society (ATS), European Respiratory Society (ERS), Japanese Respiratory Society (JRS) and Latin American Thoracic Society (ALAT) guidelines. Univariate and multivariate analyses were performed to identify factors associated to ILD and to PF-ILD. RESULTS: Of 253 patients with IIMs, 125 (49%) had ILD: 99 (78%) at IIMs diagnosis and 26 (22%) during follow-up (21/26 within 5 years). Multivariate analysis identified anti-Jo-1, anti-MDA5, anti-Ro52, high score on manual muscle test, mechanic's hands and Raynaud's phenomenon as independently associated with ILD. The predominant HRCT pattern was NSIP (50% of patients), followed by UIP (28%) and OP (22%). At 1-year follow-up, PF-ILD occurred in 18% of IIMs-ILD. PF-ILD was predicted by anti-MDA5, heliotropic rash, xerostomia and xerophthalmia at univariate but not at multivariate analysis. CONCLUSION: Patients with IIM should be carefully screened for ILD at IIMs diagnosis and yearly during follow-up. All patients with IIMs-ILD should be carefully monitored to capture ILD progression since a consistent proportion of them are expected to develop PF-ILD.
Subject(s)
Idiopathic Pulmonary Fibrosis , Lung Diseases, Interstitial , Myositis , Humans , Retrospective Studies , Prospective Studies , Lung Diseases, Interstitial/complications , Lung Diseases, Interstitial/diagnosis , Lung Diseases, Interstitial/epidemiology , Myositis/complications , Myositis/diagnosis , Myositis/epidemiologyABSTRACT
AIMS: The aim is to describe lung ultrasound (LUS) findings in a cohort of patients with suspected pulmonary tuberculosis (PTB) and compare them with computed tomography (CT) and chest x-ray (CXR) findings in order to evaluate the potentiality of LUS in TB diagnosis. METHODS: In this prospective study, 82 subjects with suspected TB were enrolled after being evaluated with CXR and chest CT. LUS was performed by blinded radiologists within 3 days after admission. A semiquantitative index was used: score 1 (lesions that extend for about 1-15% of the affected zone), score 2 (15-40%) and score 3 (40-100%). RESULTS: Microbiological analysis confirmed TB diagnosis in 58/82 (70.7%). CT was positive in all patients, LUS in 79/82 (96.3%) CXR in 78/82 (95.1%) and adding LUS and CXR in 100%. In PTB patients we found a great number of lungs zones with micronodules and with total findings than non-TPB patients (p < 0.05). Overall LUS sensitivity was 80%, greater for micronodules (82%) and nodules (95%), lower for consolidation with air bronchogram (72%) and cavitations (33%). We reported 5 complicated pleural effusion at LUS, only 1 in CT. CXR overall sensitivity was 81%. Adding CXR and LUS findings we reported a sensitivity of 90%. CONCLUSIONS: LUS could be considered a valid, non-invasive and cost-effective diagnostic tool especially in world regions where CT were not available, also in addiction with CXR. TRIAL REGISTRATION: This study was approved by the Ethics Committee of our University Hospital (rif. CEAVC 14,816).
Subject(s)
Lung , Tuberculosis, Pulmonary , Humans , Lung/diagnostic imaging , Prospective Studies , Tomography, X-Ray Computed , Tuberculosis, Pulmonary/diagnostic imaging , Ultrasonography/methods , X-RaysABSTRACT
Triage is crucial for patient's management and estimation of the required intensive care unit (ICU) beds is fundamental for health systems during the COVID-19 pandemic. We assessed whether chest computed tomography (CT) of COVID-19 pneumonia has an incremental role in predicting patient's admission to ICU. We performed volumetric and texture analysis of the areas of the affected lung in CT of 115 outpatients with COVID-19 infection presenting to the emergency room with dyspnea and unresponsive hypoxyemia. Admission blood laboratory including lymphocyte count, serum lactate dehydrogenase, D-dimer and C-reactive protein and the ratio between the arterial partial pressure of oxygen and inspired oxygen were collected. By calculating the areas under the receiver-operating characteristic curves (AUC), we compared the performance of blood laboratory-arterial gas analyses features alone and combined with the CT features in two hybrid models (Hybrid radiological and Hybrid radiomics)for predicting ICU admission. Following a machine learning approach, 63 patients were allocated to the training and 52 to the validation set. Twenty-nine (25%) of patients were admitted to ICU. The Hybrid radiological model comprising the lung %consolidation performed significantly (p = 0.04) better in predicting ICU admission in the validation (AUC = 0.82; 95% confidence interval 0.73-0.97) set than the blood laboratory-arterial gas analyses features alone (AUC = 0.71; 95% confidence interval 0.56-0.86). A risk calculator for ICU admission was derived and is available at: https://github.com/cgplab/covidapp . The volume of the consolidated lung in CT of patients with COVID-19 pneumonia has a mild but significant incremental value in predicting ICU admission.